b'Edward Raff'

research

∙ 09/12/2023

Semi-supervised Classification of Malware Families Under Extreme Class Imbalance via Hierarchical Non-Negative Matrix Factorization with Automatic Model Selection

Identification of the family to which a malware specimen belongs is esse...

0 Maksim E. Eren, et al. ∙

research

∙ 08/23/2023

A Generative Approach for Image Registration of Visible-Thermal (VT) Cancer Faces

Since thermal imagery offers a unique modality to investigate pain, the ...

0 Catherine Ordun, et al. ∙

research

∙ 07/25/2023

Exploring the Sharpened Cosine Similarity

Convolutional layers have long served as the primary workhorse for image...

0 Skyler Wu, et al. ∙

research

∙ 06/28/2023

cuSLINK: Single-linkage Agglomerative Clustering on the GPU

In this paper, we propose cuSLINK, a novel and state-of-the-art reformul...

0 Corey J. Nolet, et al. ∙

research

∙ 06/27/2023

Probing the Transition to Dataset-Level Privacy in ML Models Using an Output-Specific and Data-Resolved Privacy Profile

Differential privacy (DP) is the prevailing technique for protecting use...

0 Tyler LeBlond, et al. ∙

research

∙ 06/16/2023

You Don't Need Robust Machine Learning to Manage Adversarial Attack Risks

The robustness of modern machine learning (ML) models has become an incr...

0 Edward Raff, et al. ∙

research

∙ 06/10/2023

Vista-Morph: Unsupervised Image Registration of Visible-Thermal Facial Pairs

For a variety of biometric cross-spectral tasks, Visible-Thermal (VT) fa...

0 Catherine Ordun, et al. ∙

research

∙ 06/09/2023

AVScan2Vec: Feature Learning on Antivirus Scan Data for Production-Scale Malware Corpora

When investigating a malicious file, searching for related files is a co...

0 Robert J. Joyce, et al. ∙

research

∙ 06/06/2023

LEACE: Perfect linear concept erasure in closed form

Concept erasure aims to remove specified features from a representation....

2 Nora Belrose, et al. ∙

research

∙ 05/31/2023

Recasting Self-Attention with Holographic Reduced Representations

In recent years, self-attention has become the dominant paradigm for seq...

0 Mohammad Mahmudul Alam, et al. ∙

research

∙ 04/24/2023

Sparse Private LASSO Logistic Regression

LASSO regularized logistic regression is particularly useful for its bui...

0 Amol Khanna, et al. ∙

research

∙ 04/03/2023

Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling

How do large language models (LLMs) develop and evolve over the course o...

0 Stella Biderman, et al. ∙

research

∙ 03/18/2023

The Challenge of Differentially Private Screening Rules

Linear L_1-regularized models have remained one of the simplest and most...

0 Amol Khanna, et al. ∙

research

∙ 02/18/2023

When Visible-to-Thermal Facial GAN Beats Conditional Diffusion

Thermal facial imagery offers valuable insight into physiological states...

0 Catherine Ordun, et al. ∙

research

∙ 02/17/2023

Measuring Equality in Machine Learning Security Defenses

The machine learning security community has developed myriad defenses fo...

0 Luke E. Richards, et al. ∙

research

∙ 01/15/2023

A Coreset Learning Reality Check

Subsampling algorithms are a natural approach to reduce data size before...

0 Fred Lu, et al. ∙

research

∙ 12/05/2022

Efficient Malware Analysis Using Metric Embeddings

In this paper, we explore the use of metric learning to embed Windows PE...

0 Ethan M. Rudd, et al. ∙

research

∙ 11/23/2022

Lempel-Ziv Networks

Sequence processing has long been a central area of machine learning res...

0 Rebecca Saul, et al. ∙

research

∙ 11/03/2022

Crosslingual Generalization through Multitask Finetuning

Multitask prompted finetuning (MTF) has been shown to help large languag...

0 Niklas Muennighoff, et al. ∙

research

∙ 10/16/2022

A General Framework for Auditing Differentially Private Machine Learning

We present a framework to statistically audit the privacy guarantee conf...

0 Fred Lu, et al. ∙

research

∙ 09/05/2022

Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training

The quantification of uncertainty is important for the adoption of machi...

0 Derek Everett, et al. ∙

research

∙ 06/13/2022

Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations

Due to the computational cost of running inference for a neural network,...

9 Mohammad Mahmudul Alam, et al. ∙

research

∙ 06/09/2022

Neural Bregman Divergences for Distance Learning

Many metric learning tasks, such as triplet learning, nearest neighbor r...

0 Fred Lu, et al. ∙

research

∙ 06/07/2022

Marvolo: Programmatic Data Augmentation for Practical ML-Driven Malware Detection

Data augmentation has been rare in the cyber security domain due to tech...

0 Michael D. Wong, et al. ∙

research

∙ 04/18/2022

VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance

Generating and editing images from open domain text prompts is a challen...

1 Katherine Crowson, et al. ∙

research

∙ 04/09/2022

A Siren Song of Open Source Reproducibility

As reproducibility becomes a greater concern, conferences have largely c...

0 Edward Raff, et al. ∙

research

∙ 04/08/2022

Does the Market of Citations Reward Reproducible Work?

The field of bibliometrics, studying citations and behavior, is critical...

0 Edward Raff, et al. ∙

research

∙ 04/07/2022

Intelligent Sight and Sound: A Chronic Cancer Pain Dataset

Cancer patients experience high rates of chronic pain throughout the tre...

0 Catherine Ordun, et al. ∙

research

∙ 02/28/2022

Proceedings of the Artificial Intelligence for Cyber Security (AICS) Workshop at AAAI 2022

The workshop will focus on the application of AI to problems in cyber se...

0 James Holt, et al. ∙

research

∙ 02/18/2022

Out of Distribution Data Detection Using Dropout Bayesian Neural Networks

We explore the utility of information contained within a dropout based B...

0 Andre T. Nguyen, et al. ∙

research

∙ 02/14/2022

Continuously Generalized Ordinal Regression for Linear and Deep Models

Ordinal regression is a classification task where classes have an order ...

0 Fred Lu, et al. ∙

research

∙ 01/19/2022

Neural Language Models are Effective Plagiarists

As artificial intelligence (AI) technologies become increasingly powerfu...

0 Stella Biderman, et al. ∙

research

∙ 12/28/2021

Rank-1 Similarity Matrix Decomposition For Modeling Changes in Antivirus Consensus Through Time

Although groups of strongly correlated antivirus engines are known to ex...

0 Robert J. Joyce, et al. ∙

research

∙ 12/27/2021

Bridging the Gap: Using Deep Acoustic Representations to Learn Grounded Language from Percepts and Raw Speech

Learning to understand grounded language, which connects natural languag...

0 Gaoussou Youssouf Kebe, et al. ∙

research

∙ 11/29/2021

MOTIF: A Large Malware Reference Dataset with Ground Truth Family Labels

Malware family classification is a significant issue with public safety ...

0 Robert J. Joyce, et al. ∙

research

∙ 09/23/2021

A Framework for Cluster and Classifier Evaluation in the Absence of Reference Labels

In some problem spaces, the high cost of obtaining ground truth labels n...

0 Robert J. Joyce, et al. ∙

research

∙ 09/23/2021

Adversarial Transfer Attacks With Unknown Data and Class Overlap

The ability to transfer adversarial attacks from one model (the surrogat...

3 Luke E. Richards, et al. ∙

research

∙ 09/05/2021

Learning with Holographic Reduced Representations

Holographic Reduced Representations (HRR) are a method for performing sy...

0 Ashwinkumar Ganesan, et al. ∙

research

∙ 08/09/2021

Leveraging Uncertainty for Improved Static Malware Detection Under Extreme False Positive Constraints

The detection of malware is a critical task for the protection of comput...

0 Andre T. Nguyen, et al. ∙

research

∙ 06/15/2021

Generating Thermal Human Faces for Physiological Assessment Using Thermal Sensor Auxiliary Labels

Thermal images reveal medically important physiological information abou...

0 Catherine Ordun, et al. ∙

research

∙ 06/15/2021

Evading Malware Classifiers via Monte Carlo Mutant Feature Discovery

The use of Machine Learning has become a significant part of malware det...

0 John Boutsikas, et al. ∙

research

∙ 05/06/2021

Exact Acceleration of K-Means++ and K-Means

K-Means++ and its distributed variant K-Means have become de facto tools...

0 Edward Raff, et al. ∙

research

∙ 04/13/2021

Semiring Primitives for Sparse Neighborhood Methods on the GPU

High-performance primitives for mathematical operations on sparse vector...

19 Corey J. Nolet, et al. ∙

research

∙ 03/01/2021

Accounting for Variance in Machine Learning Benchmarks

Strong empirical evidence that one machine-learning algorithm A outperfo...

23 Xavier Bouthillier, et al. ∙

research

∙ 12/17/2020

Research Reproducibility as a Survival Analysis

There has been increasing concern within the machine learning community ...

0 Edward Raff, et al. ∙

research

∙ 12/17/2020

Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection

Recent works within machine learning have been tackling inputs of ever-i...

14 Edward Raff, et al. ∙

research

∙ 11/16/2020

Sampling Approach Matters: Active Learning for Robotic Language Acquisition

Ordering the selection of training data using active learning can lead t...

0 Nisha Pillai, et al. ∙

research

∙ 10/22/2020

Getting Passive Aggressive About False Positives: Patching Deployed Malware Detectors

False positives (FPs) have been an issue of extreme importance for anti-...

0 Edward Raff, et al. ∙

research

∙ 09/22/2020

The Use of AI for Thermal Emotion Recognition: A Review of Problems and Limitations in Standard Design and Data

With the increased attention on thermal imagery for Covid-19 screening, ...

7 Catherine Ordun, et al. ∙

research

∙ 09/06/2020

Automatic Yara Rule Generation Using Biclustering

Yara rules are a ubiquitous tool among cybersecurity practitioners and a...

0 Edward Raff, et al. ∙

Edward Raff

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